Mathew Roxy

Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land-sea thermal gradient

There are large uncertainties looming over the status and fate of the South Asian summer monsoon, with several studies debating whether the monsoon is weakening or strengthening in a changing climate. Our analysis using multiple observed datasets demonstrates a significant weakening trend in summer rainfall during 1901-2012 over the central-east and northern regions of India, along the Ganges-Brahmaputra-Meghna basins and the Himalayan foothills, where agriculture is still largely rain-fed. Earlier studies have suggested an increase in moisture availability and land-sea thermal gradient in the tropics due to anthropogenic warming, favouring an increase in tropical rainfall. Here we show that the land-sea thermal gradient over South Asia has been decreasing, due to rapid warming in the Indian Ocean and a relatively subdued warming over the subcontinent. Using long-term observations and coupled model experiments, we provide compelling evidence that the enhanced Indian Ocean warming potentially weakens the land-sea thermal contrast, dampens the summer monsoon Hadley circulation, and thereby reduces the rainfall over parts of South Asia.

The Curious Case of Indian Ocean Warming

AbstractRecent studies have pointed out an increased warming over the Indian Ocean warm pool (the central-eastern Indian Ocean characterized by sea surface temperatures greater than 28.0°C) during the past half-century, although the reasons behind this monotonous warming are still debated. The results here reveal a larger picture—namely, that the western tropical Indian Ocean has been warming for more than a century, at a rate faster than any other region of the tropical oceans, and turns out to be the largest contributor to the overall trend in the global mean sea surface temperature (SST). During 1901–2012, while the Indian Ocean warm pool went through an increase of 0.7°C, the western Indian Ocean experienced anomalous warming of 1.2°C in summer SSTs. The warming of the generally cool western Indian Ocean against the rest of the tropical warm pool region alters the zonal SST gradients, and has the potential to change the Asian monsoon circulation and rainfall, as well as alter the marine food webs in t...

A reduction in marine primary productivity driven by rapid warming over the tropical Indian Ocean

Among the tropical oceans, the western Indian Ocean hosts one of the largest concentrations of marine phytoplankton blooms in summer. Interestingly, this is also the region with the largest warming trend in sea surface temperatures in the tropics during the past century—although the contribution of such a large warming to productivity changes has remained ambiguous. Earlier studies had described the western Indian Ocean as a region with the largest increase in phytoplankton during the recent decades. On the contrary, the current study points out an alarming decrease of up to 20% in phytoplankton in this region over the past six decades. We find that these trends in chlorophyll are driven by enhanced ocean stratification due to rapid warming in the Indian Ocean, which suppresses nutrient mixing from subsurface layers. Future climate projections suggest that the Indian Ocean will continue to warm, driving this productive region into an ecological desert.

Impacts of Indian and Atlantic oceans on ENSO in a comprehensive modeling framework

Abstract The impact of the Indian and Atlantic oceans variability on El Niño–Southern-Oscillation (ENSO) phenomenon is investigated through sensitivity experiments with the SINTEX-F2 coupled model. For each experiment, we suppressed the sea surface temperature (SST) variability in either the Indian or Atlantic oceans by applying a strong nudging of the SST toward a SST climatology computed either from a control experiment or observations. In the sensitivity experiments where the nudging is done toward a control SST climatology, the Pacific mean state and seasonal cycle are not changed. Conversely, nudging toward an observed SST climatology in the Indian or Atlantic domain significantly improves the mean state and seasonal cycle, not only in the nudged domain, but also in the whole tropics. These experiments also demonstrate that decoupling the Indian or Atlantic variability modifies the phase-locking of ENSO to the annual cycle, influences significantly the timing and processes of ENSO onset and termination stages, and, finally, shifts to lower frequencies the main ENSO periodicities. Overall, these results suggest that both the Indian and Atlantic SSTs have a significant damping effect on ENSO variability and promote a shorter ENSO cycle. The reduction of ENSO amplitude is particularly significant when the Indian Ocean is decoupled, but the shift of ENSO to lower frequencies is more pronounced in the Atlantic decoupled experiments. These changes of ENSO statistical properties are related to stronger Bjerknes and thermocline feedbacks in the nudged experiments. During the mature phase of El Niño events, warm SST anomalies are found over the Indian and Atlantic oceans in observations or the control run. Consistent with previous studies, the nudged experiments demonstrate that these warm SSTs induce easterly surface wind anomalies over the far western equatorial Pacific, which fasten the transition from El Niño to La Niña and promote a shorter ENSO cycle in the control run. These results may be explained by modulations of the Walker circulation induced directly or indirectly by the Indian and Atlantic SSTs. Another interesting result is that decoupling the Atlantic or Indian oceans change the timing of ENSO onset and the relative role of other ENSO atmospheric precursors such as the extra-tropical Pacific Meridional Modes or the Western North Pacific SSTs.

The IITM earth system model

AbstractWith the goal of building an Earth system model appropriate for detection, attribution, and projection of changes in the South Asian monsoon, a state-of-the-art seasonal prediction model, namely the Climate Forecast System version 2 (CFSv2) has been adapted to a climate model suitable for extended climate simulations at the Indian Institute of Tropical Meteorology (IITM), Pune, India. While the CFSv2 model has been skillful in predicting the Indian summer monsoon (ISM) on seasonal time scales, a century-long simulation with it shows biases in the ocean mixed layer, resulting in a 1.5°C cold bias in the global mean surface air temperature, a cold bias in the sea surface temperature (SST), and a cooler-than-observed troposphere. These biases limit the utility of CFSv2 to study climate change issues. To address biases, and to develop an Indian Earth System Model (IITM ESMv1), the ocean component in CFSv2 was replaced at IITM with an improved version, having better physics and interactive ocean biogeo...

A threefold rise in widespread extreme rain events over central India

Socioeconomic challenges continue to mount for half a billion residents of central India because of a decline in the total rainfall and a concurrent rise in the magnitude and frequency of extreme rainfall events. Alongside a weakening monsoon circulation, the locally available moisture and the frequency of moisture-laden depressions from the Bay of Bengal have also declined. Here we show that despite these negative trends, there is a threefold increase in widespread extreme rain events over central India during 1950–2015. The rise in these events is due to an increasing variability of the low-level monsoon westerlies over the Arabian Sea, driving surges of moisture supply, leading to extreme rainfall episodes across the entire central subcontinent. The homogeneity of these severe weather events and their association with the ocean temperatures underscores the potential predictability of these events by two-to-three weeks, which offers hope in mitigating their catastrophic impact on life, agriculture and property.Against the backdrop of a declining monsoon, the number of extreme rain events is on the rise over central India. Here the authors identify a threefold increase in widespread extreme rains over the region during 1950–2015, driven by an increasing variability of the low-level westerlies over the Arabian Sea.

Spatiotemporal characteristics of seasonal to multidecadal variability of pCO2 and air‐sea CO2 fluxes in the equatorial Pacific Ocean

Seasonal, interannual, and multidecadal variability of seawater pCO2 and air-sea CO2 fluxes in the equatorial Pacific Ocean for the past 45 years (1961–2005) are examined using a suite of experiments performed with an offline biogeochemical model driven by reanalysis ocean products. The processes we focus on are: (a) the evolution of seasonal cycle of pCO2 and air-sea CO2 fluxes during the dominant interannual mode in the equatorial Pacific, i.e., the El Nino-Southern Oscillation (ENSO), (b) its spatiotemporal characteristics, (c) the combined and individual effects of wind and ocean dynamics on pCO2 and CO2 flux variability and their relation to canonical (eastern Pacific) and central Pacific (Modoki) ENSOs and (d) the multidecadal variability of carbon dynamics in the equatorial Pacific and its association with the Pacific Decadal Oscillations (PDO). The simulated mean and seasonal cycle of pCO2 and CO2 fluxes are comparable with the observational estimates and with other model results. A new analysis methodology based on the traditional Empirical Orthogonal Functions (EOF) applied over a time-time domain is employed to elucidate the dominant mode of interannual variability of pCO2 and air-sea CO2 fluxes at each longitude in the equatorial Pacific. The results show that the dominant interannual variability of CO2 fluxes in the equatorial Pacific (averaged over 5°N–10°S) coevolves with that of ENSO. Generally a reduced CO2 source in the central-to-eastern equatorial Pacific evident during June–July of the El Nino year (Year:0) peaks through September of Year:0 to February of Year:+1 and recovers to a normal source thereafter. In the region between 160°W and 110°W, the canonical El Nino controls the dominant variability of CO2 fluxes (mean and RMS of anomaly from 1961 to 2005 is 0.43±0.12 PgC yr−1). However, in the western (160°E–160°W) and far eastern (110°W–90°W) equatorial Pacific, CO2 flux variability is dominantly influenced by the El Nino-Modoki (0.3±0.06 and 0.11±0.04 PgC yr−1, respectively). On the other hand, the interannual variability of pCO2 is correlated with the canonical El Nino mostly to the east of 140°W and with El Nino-Modoki to the west of 140°W. Decoupling of CO2 flux and pCO2 variability at various locations in the equatorial Pacific is attributable to the differences in the combined and individual effects of ocean dynamics and winds associated with these two types of ENSO. A multidecadal variability in the equatorial Pacific sea-air CO2 fluxes and pCO2 exhibits a positive phase during the 1960s, a negative phase during the 1980s, and then positive again by the 2000s. Within the ocean, the dissolved inorganic carbon (DIC) anomalies are traceable to the northern Pacific via thermocline pathways at decadal timescales. The multidecadal variability of equatorial Pacific CO2 fluxes and pCO2 are determined by the phases of the PDO and the corresponding scale of the El Nino-Modoki variability, whereas canonical El Ninos contribution is to mainly determine the variability at interannual timescales. This study segregates the impacts of different types of ENSOs on the equatorial Pacific carbon cycle and sets the framework for analysing its spatiotemporal variability under global warming.

Processes Associated with the Tropical Indian Ocean Subsurface Temperature Bias in a Coupled Model

AbstractSubsurface temperature biases in coupled models can seriously impair their capability in generating skillful seasonal forecasts. The National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), coupled model, which is used for seasonal forecast in several countries including India, displays warm (cold) subsurface (surface) temperature bias in the tropical Indian Ocean (TIO), with deeper than observed mixed layer and thermocline. In the model, the maximum warm bias is reported between 150- and 200-m depth. Detailed analysis reveals that the enhanced vertical mixing by strong vertical shear of horizontal currents is primarily responsible for TIO subsurface warming. Weak upper-ocean stability corroborated by surface cold and subsurface warm bias further strengthens the subsurface warm bias in the model. Excess inflow of warm subsurface water from Indonesian Throughflow to the TIO region is partially contributing to the warm bias mainly over the southern TIO region....

Indian Ocean and Indian summer monsoon: relationships without ENSO in ocean–atmosphere coupled simulations

The relationship between the Indian Ocean and the Indian summer monsoon (ISM) and their respective influence over the Indo-Western North Pacific (WNP) region are examined in the absence of El Niño Southern Oscillation (ENSO) in two partially decoupled global experiments. ENSO is removed by nudging the tropical Pacific simulated sea surface temperature (SST) toward SST climatology from either observations or a fully coupled control run. The control reasonably captures the observed relationships between ENSO, ISM and the Indian Ocean Dipole (IOD). Despite weaker amplitude, IODs do exist in the absence of ENSO and are triggered by a boreal spring ocean–atmosphere coupled mode over the South-East Indian Ocean similar to that found in the presence of ENSO. These pure IODs significantly affect the tropical Indian Ocean throughout boreal summer, inducing a significant modulation of both the local Walker and Hadley cells. This meridional circulation is masked in the presence of ENSO. However, these pure IODs do not significantly influence the Indian subcontinent rainfall despite overestimated SST variability in the eastern equatorial Indian Ocean compared to observations. On the other hand, they promote a late summer cross-equatorial quadrupole rainfall pattern linking the tropical Indian Ocean with the WNP, inducing important zonal shifts of the Walker circulation despite the absence of ENSO. Surprisingly, the interannual ISM rainfall variability is barely modified and the Indian Ocean does not force the monsoon circulation when ENSO is removed. On the contrary, the monsoon circulation significantly forces the Arabian Sea and Bay of Bengal SSTs, while its connection with the western tropical Indian Ocean is clearly driven by ENSO in our numerical framework. Convection and diabatic heating associated with above-normal ISM induce a strong response over the WNP, even in the absence of ENSO, favoring moisture convergence over India.

Coupled Land‐Atmosphere Regional Model Reduces Dry Bias in Indian Summer Monsoon Rainfall Simulated by CFSv2

Global climate models including the Climate Forecast System version 2, the operational model used for prediction of Indian summer monsoon rainfall by the India Meteorological Department, has dry precipitation bias, mostly over densely populated Ganga basin. This restricts the use of model output in hydrological simulations/forecasts. We use regional atmospheric Weather Research and Forecasting model coupled with land surface models, driven by the boundary conditions from Climate Forecast System version 2. We find significant reduction in the dry bias of Indian summer monsoon rainfall with regional land-atmosphere model and this attributes to (a) improved moisture transport from Western and Upper Indian Ocean to Ganga Basin and (b) improved precipitation recycling over the Ganga basin. We find that the smoothened topography in the global model allows advection of cold dry subtropical air into the Indian monsoon region, contributing to the cold temperature and dry precipitation bias. These results have important implications for monsoon simulations in developing operational hydroclimatic prediction system in India. Plain Language Summary The operational monsoon prediction model for India, Climate Forecast System version 2, has significant dry bias in precipitation over the Ganga basin, and this restricts the use of model output for hydrologic prediction. We attribute such bias to the lack of representation of land surface processes and characteristics in the model. We show that an improved representation of land characteristics in a regional coupled atmospheric-land model improves not only the land-atmosphere interactions but also the moisture contributions from distant oceanic sources. This finally results into improved simulations of monsoon.